Overview

This is a graduate-level course on optimization. The course covers
mathematical programming and combinatorial optimization from the
perspective of convex optimization, which is a central tool for solving
large-scale problems. In recent years convex optimization has had
a profound impact on statistical machine learning, data analysis,
mathematical finance, signal processing, control, theoretical computer science, and many other areas. The first part will be
dedicated to the theory of convex optimization and its direct
applications. The second part will focus on advanced techniques in
combinatorial optimization using machinery developed in the first
part.